I. Field
The present disclosure relates generally to communication, and more specifically to techniques for estimating signal quality in a communication system.
II. Background
In a communication system, a transmitter typically processes (e.g., encodes and symbol maps) traffic data to generate data symbols, which are modulation symbols for data. The transmitter then processes the data symbols to generate a modulated signal and transmits this signal via a communication channel. The communication channel distorts the transmitted signal with a channel response and further degrades the signal with noise and interference. A receiver receives the transmitted signal and processes the received signal to obtain detected symbols, which are estimates of the transmitted data symbols. The receiver then processes (e.g., demodulates and decodes) the detected symbols to obtain decoded data.
The receiver typically estimates the quality of the received signal. Signal quality may be quantified by signal-to-noise ratio (SNR), signal-to-noise-and-interference ratio (SINR), energy-per-symbol-to-noise ratio (Es/No), and so on. The signal quality estimates may be used for various purposes. For example, the signal quality estimates may be used in the decoding process, e.g., to give greater weight to higher quality detected symbols and less weight to lower quality detected symbols. The signal quality estimates may also be used to select a suitable rate for data transmission. The system may support a set of rates, and each supported rate may require a certain minimum signal quality for reliable reception. The highest rate that can be reliably received may be selected based on the signal quality estimates. Accurate signal quality estimates may thus improve decoding performance, enhance throughput, reduce latency, and provide other benefits.
There is therefore a need in the art for techniques to accurately estimate signal quality in a communication system.